1. Field of the Invention
The embodiments of the invention provide methods, computer program products, etc. for autonomic retention classes when retaining data within storage devices.
2. Description of the Related Art
Storage ingestion rates are very high in large clustered system storage environments. This causes finite storage resources to be constrained. The amount of accumulated data is so large that there is a need to prioritize the data that is actually stored within the system. Large clustered storage environments are becoming more common in larger contemporary storage area network (SAN) and network-attached storage (NAS) systems (e.g., SAN.FS deployment in CERN).
With the growing need for storage consolidation, applications compete amongst themselves for resources in the shared storage architecture. The cumulative resource requirements of such applications far exceed what the storage system is capable of supporting. It is thus required to assign a “priority value” to the data generated by different applications—the assignment should be generated in an automated fashion, with minimal human intervention. Existing approaches in this domain are primarily based on understanding the semantics of the data (i.e., the data is an image of a gold mine or a new article for alternative medicine). This approach is error-prone, limited, and relatively manual. The term “resource” is instantiated as capacity herein, but the concepts are equally applicable to storage performance bandwidth.